To get to the restaurant table, food must travel great lengths to preserve that farm fresh quality and in many cases, IoT-enabled sensors are being used to do this. This is especially important as the World Health Organization estimates that one in 10 people fall ill every year from eating contaminated food.
When we think of our favorite dish, we often associate it with delicious flavors, pleasant scents and even memories of a night out with friends. What we likely don’t consider is technology, something that’s critical in ensuring the meal on our plate is safe to consume. Technology plays an essential role in guaranteeing that restaurants are serving fresh food to customers. From identifying operational deficiencies to protecting the overall brand of an organization, there are certain measures restaurants are taking—whether local or country-wide chains—to ensure food quality remains a top priority.
Restaurants are perhaps held to an even higher standard than your local supermarket when it comes to the quality of food on the table. Therefore, it’s imperative that perishables are cared for properly throughout the entirety of the food supply chain and that starts well before the food ever enters the restaurant’s front door. With long-range, low-power wireless IoT technology, farmers can get insights into a number of variables that may impact the growth of their crops. Armed with that knowledge, they can make real-time decisions to optimize crop growth and ultimately produce a greater yield. For example, farmers today can set up a series of sensors throughout their farm to measure real-time soil conditions, including humidity and pH levels. If they notice an especially high pH, for example, they can immediately remedy the situation and provide the crop with the proper nutrients or conditions it needs to grow.
For food safely to arrive at restaurants, it must be kept in a controlled environment during its journey from the farm or warehouse, and carefully monitored during that time. The temperature of refrigerated shipping units or storage facilities is an incredibly important factor, as bacteria growth can increase even by simply opening the refrigerator door or with a slight temperature shift, and employees are often tasked with managing this. With large facilities comes increased labor for employees, which can lead to inefficient temperature monitoring. To eliminate food waste and contamination, IoT sensors deployed throughout facilities can eliminate human error, and deliver more consistent monitoring, via real-time updates when temperatures enter unsafe territories.
Numerous international food handling and food safety laws have been implemented to reduce the risk of foodborne illness resulting from bacterial growth. A major component of most “farm-to-fork” regulations is the ability to track, report and maintain appropriate temperature conditions inside refrigeration and freezer units throughout the entire cold chain—including when the food finally makes it the restaurant.
This is a universal priority for restaurants around the world, including Hattie B’s Hot Chicken, a southern-style food chain, which started in Nashville and now has locations nationwide. To successfully do this, the restaurant turned to technology. They used a supplier of wireless connectivity solutions with integrated long range, low power technology for temperature monitoring sensors. The sensors, which are capable of penetrating stainless steel doors and concrete walls, can monitor temperatures in refrigerators and freezers. This is essential, as the technology eliminates possible human error in manually checking temps and other food safety procedures. In instances where refrigerator temperatures shift out of range, the technology remotely notifies restaurant managers in real-time, allowing them to act quickly, ensuring their perishables remain fresh and safe for customers at all times.
Food waste in restaurants is closely tied to food safety. In the United States alone, food waste is estimated to be between 30–40% of the food supply, according to the USDA. In the restaurant industry in particular, human error is one of the most notable reasons for food waste. To eliminate the human error when handling food and monitoring storage, an IoT solution provider for the industrial, smart city and smart energy segments, integrated long-range low power technology into smart refrigeration solutions for restaurant applications. This IoT solution is designed for humidity and temperature monitoring, delivering real-time updates to managers to ensure the shelf life of food is maximized and it remains safe to consume, ultimately leading to a decrease in food waste.
From farm to table, technology plays an essential role in ensuring restaurants are delivering the highest quality of fresh, safe food. It allows organizations to identify operational deficiencies and reduce overall food safety risk, which is imperative when maintaining a strong business in a competitive industry.
Food safety remains a top-of-mind concern for food manufacturers, especially considering some of the top recalls in 2019 were caused by bacteria contamination—including Listeria and E. coli. Every aspect of the plant operation, from maintenance to executives, to junior staff and quality control, holds both responsibility and concern in producing safe food. Unfortunately, there’s a lot at stake when plant operations’ sanitation programs run into issues, which can cause health threats.
While the rapid explosion of new innovations complements our daily lives in efficiency and convenience, plant operations may find difficulty in keeping up-to-speed with new technology such as robotics, drones and automated applications. When facilities’ equipment becomes more and more outdated, it poses food safety challenges around cleaning, maintenance and upgrades.
Luckily, in some cases, innovation is becoming much easier to deploy. Opportunities abound for food processing plants to integrate new technologies into their operations to deliver significant returns on investment while simultaneously enhancing sanitation, safety and production efficiency on the plant floor.
The Dangers with Today’s Practices
There are many pitfalls with older, more traditional cleaning techniques. In a place where cleanliness is critical to food safety and public health around the world, the industry understands sanitation means more than just scrubbing, mopping and wiping. While these are important daily practices to be done around the processing plant, there are still concerns on whether this kind of intermittent cleaning is truly enough to keep surfaces completely sanitized—knowing that continuous cleaning around the clock seems impractical in any facilities.
Unfortunately, there are many areas, some very hard to reach, for bacteria and other pathogens to live and spread around a processing plant. Zone 1, which holds the conveyor belt and other common high-touch points, consistently comes into contact with food, chemicals and humans. However, for processors to reduce the likelihood of contaminated food, they must consider areas outside of Zone 1 as well—including employee break rooms, hallways and bathrooms—to implement automated sanitation technologies. Additionally, the most common food contaminants, such as Listeria, Salmonella and E. coli, are usually invisible to the naked eye. Therefore, plants need to employ automated technology to continuously kill microscopic bacteria, mold and fungi to prevent regrowth and ensure clean food and equipment.
Looking to New Tech to Fight Germs
When looking to upgrade a plant operation facility, automated technology should be top-of-mind. Automated food production technologies solve two main problems: Food safety and sanitation efficiency. Wash-down robotic systems work to prevent food contamination, while other automated robots complete tasks on the production floor such as packaging, transporting and lifting. With the CDC estimating that roughly one in six Americans suffer from foodborne illnesses, the need for improved sanitation design is integral.
In today’s age, there are several ways to achieve heightened cleanliness by incorporating automation and robotics into production lines. Slicers, dicers and cutters are manufactured with hygienic design in mind. Smart cleaning equipment can automatically store various cleaning steps. Data tracking applications can monitor sanitation steps and ensure all boxes are checked throughout the cleaning program.
Incorporating antimicrobial LED lighting ensures sanitation is truly integrated into the facility’s design—working continually 24/7 to kill and prevent bacteria, and its growth while also serving a dual purpose of both antimicrobial protection and a proper source of illumination. As is the case with this type of technology, once these lights are installed, it becomes an easy, hands-free way of reducing labor, chemicals and, in many cases, work stoppages.
According to Meticulous Research, the global food automation market is expected to be worth $14.3 billion by 2025. With automation set to explode, it’s important for leaders in the food and beverage industry to take advantage of safety tech innovations to advance sanitation around the processing plant. Facility upgrades to improve, enhance and automate sanitation could impact food manufacturers in the long-term by decreasing costs, preventing recalls, improving brand value, gaining consumer trust, minimizing risk and impacting the bottom line.
Join Food Safety Tech next week for the first in a series of complimentary webinars, called Drivers in Food Safety Testing, about the important components and issues that encompass food safety testing. Angela Anandappa, Ph.D., founding director of the Alliance for Advanced Sanitation and member of the FST Advisory Board, will lead the discussion with a presentation about Technologies Leading the Way. The complimentary webinar is aimed at food safety professionals within quality assurance and control, compliance, food lab and contract lab management, and risk management. A technology spotlight given by Lyssa Sakaley, senior global product manager for molecular pathogen testing at MilliporeSigma will follow Anandappa’s presentation. The event will conclude with an interactive Q&A with attendees.
Drivers in Food Safety Testing: Technologies Leading the Way
Wednesday, March 18 at 1 pm ET Register now!
The popularity of plant-based protein powders has skyrocketed, and so has fraudulent activity with so-called protein boosting adulterants. Examples are a variety of beans, such as fava beans, as well as wheat, maize, alfalfa and more. Due to the rapid innovation and development of novelty supplements, regulatory standards are in urgent need of overhaul. Correct ingredient investigation in commercial plant-based protein powders is therefore a must and was investigated in this study with three different diagnostic tools.
Haven’t mastered your pest management processes yet? Don’t miss next week’s complimentary webinar, “New Technology’s Impact on Pest Management in the FSMA Regulated World”. Steven Sklare, president of Food Safety Academy, will guide attendees through how technology can help with FSMA compliance, namely as it relates to pest management. He will also discuss how the IoT has made the mouse trap concept smarter, and how you can use this to your advantage in your company’s facility.
The event, which takes place Thursday, March 5 at 12 pm ET, is sponsored by Bayer Digital Pest Management.
On March 29, 2018, FDA announced the Nutrition Innovation Strategy, which signaled their intention to take a fresh look at what can be done to “reduce the burden of chronic disease through improved public nutrition.” The agency wants to facilitate consumers making better food choices to improve their health. At the same time, FDA has acknowledged that in many cases, changes in food processing technology has rendered outdated certain provisions of the regulations once written to both inform and protect the public. Therefore, FDA has developed a plan to move ahead to update its policy toolkit.
This multi-pronged approach includes modernizing food labeling, including food standards, health claims policy, ingredient labeling requirements and continuing implementation of the updated nutrition facts label, menu labeling, and reducing sodium in processed food products.
In particular, in trying to gather information to help determine the best approach to revising food standards of identity, FDA held a public meeting on September 27, 2019. FDA is attempting to provide room in the regulations for industry to be able to use modern and hopefully more healthful manufacturing methods while at the same time retaining the traditional characteristics and nutritional value of standardized food products.
During the public meeting, consumer advocacy groups, food industry trade groups and medical associations expressed many points of view as to what FDA should do to make the more than 250 food standards of identity more applicable to the modern food supply. FDA also took comments on updating food ingredient labeling requirements, including simplifying terms for ingredients such as vitamins. Because each food standard of identity is a regulation, it will be no small effort for the agency to update, remove or add standards of identity as needed. This meeting was a way to get input to help guide their decisions and priority—making for food standards and ingredient labeling revisions.
Obviously, with such a broad-based effort, the revisions and changes will be incremental. But the thing to keep in mind is that it all points to an effort to improve public health through the food supply as well as an effort to impactfully modernize the regulations. What follows is a very brief summary of some of FDA’s recent actions in this regard.
On December 30, 2019, FDA announced the final guidance on Serving Sizes, Dual-Column Labeling, which provided additional information about when dual column labeling for nutrition is required and what exemptions are in place to provide relief for certain products or package sizes.
On December 27, 2019, FDA reopened the comment period on the use of ultrafiltered (UF) milk in certain cheeses. When the proposed rule for UF milk in cheeses originally published in 2005, FDA received many comments. Essentially, ultrafiltration was a means to enhance the speed of cheese production, and the standard of identity cheeses were written before this technology was common and did not permit this type of process. FDA seeks to modernize the cheese standards while keeping intact the nature of these cheeses, and so the agency is eager to learn about what can be done to accommodate the new technology without losing the essence of the standards that consumers have come to expect. Because of the time lapse since the previous comment period, FDA is seeking more information to inform their rulemaking.
On October 25, 2019, FDA released a final rule revising the type size for calorie declarations on front of pack labeling for glass-front vending machines. The 2014 rule establishing calorie labeling for products sold from vending machines had provisions that were difficult for certain products to meet. This new rule recognizes those challenges and was an attempt by the agency to provide a middle ground for the industry to meet the requirements of visible calorie labeling on small packages sold in vending machines.
On August 15, 2019, FDA announced final guidance on converting units of measure for Folate, Niacin, and Vitamins A, D and E on the nutrition and supplement facts labels. The guidance provides help to the industry in meeting the requirements of the revised nutrition facts label.
Regarding updating the “healthy” claim on food products, when this term was originally defined by the agency, saturated fat was the nutrient of focus for these claims. However, since then, there are new focuses on health, such as added sugar and calories. In September 2016, FDA sought to modernize the claim, and provided an interim policy to guide its use.
In May 2019, FDA published a draft guidance to provide enforcement discretion for the use of the term “potassium chloride salt” on ingredient statements. In addition, in April 2019, FDA provided a draft guidance for the calculation of calories from a newer sweetener, Allulose.
As you can see, there are a lot of moving parts to FDA’s effort. What will be the impact on the food industry? Changes will most likely be gradual. Over time, there will be modifications to food standards of identity, and potentially claims, and both of these will cause label revisions. And, typically, there may be enforcement discretion by FDA to allow the industry time to revise their products and /or labeling as needed.
You will see FDA requests for information from the public and the industry on various related topics to the Nutrition Innovation Strategy, and guidance documents will be updated.
Unfortunately, alcoholic beverages are also prone to fraud involving the addition of substances that can cause illness or death. This often happens at the local level, with the production of “moonshine” or other unlicensed spirits. Some of the substances used have included methanol, isopropyl alcohol and industrial-grade alcohol.
One notable incident from the 1980s had global implications and severe market effects. Diethylene glycol was added to Austrian wines, resulting in recalls around the world when the adulteration was detected. Fortunately, no illnesses or deaths were reported. Just a year later, methanol added to Italian wine caused both hospitalizations and deaths. More recently, incidents involving the addition of methanol to spirits have caused deaths in India, China and Malaysia.
Authentication and traceability for alcoholic beverages, and specifically wines, lend themselves to technology-enabled solutions such as blockchain. On a lighter note, take a look at some of the labels documented by reporters covering the wine market in China. In a high value marketplace such as the wine business, there is no end to creativity in labeling.
As machines become more intelligent, every industry on earth will find abundant new applications and ways to benefit. For the food industry, which has an incredible number of moving parts and is especially risk-averse, machine vision and machine learning are especially valuable additions to the supply chain.
The following is a look at what machine vision is, how it can play a role in manufacturing and distributing foods and beverages, and how employers can train workers to get the most out of this exciting technology.
What Is Machine Vision?
Machine vision isn’t a brand-new concept. Cameras and barcode readers with machine vision have long been capable of reading barcodes and QR codes and verifying that products have correct labels. Modern machine vision takes the concept to new levels of usefulness.
Barcodes and product identifiers have a limited set of known configurations, which makes it relatively straightforward to program an automated inspection station to recognize, sort or reject products as necessary. Instead, true machine vision means handlers don’t have to account for every potential eventuality. Machine vision instead learns over time, based on known parameters, to differentiate between degrees of product damage.
Consider the problem of appraising an apple for its salability. Is it bruised or discolored? Machine vision recognizes that no two bruises look precisely alike. There’s also the matter of identifying different degrees of packaging damage. To tackle these problems, it’s not possible to program machine vision to recognize a fixed set of visual clues. Instead, its programming must interpret its surroundings and make a judgment about what it sees.
The neural networks that power machine vision have a wide range of applications, including improving pathfinding abilities for robots. In this article, I’ll focus on how to leverage machine vision to improve the quality of edible products and the profitability of the food and beverage industry.
Applications for Machine Vision in the Food Industry
There are lots of ways to apply machine vision to a food processing environment, with new variations on the technology cropping up regularly. The following is a rundown on how different kinds of machine vision systems serve different functions in the food and beverage sector.
1. Frame Grabbing and 3-D Machine Vision
Machine vision systems require optimal lighting to carry out successful inspections. If part of the scanning environment lies in shadow, undesirable products might find their way onto shelves and into customers’ homes.
Food products sometimes have unique needs when it comes to carrying out visual inspections. It’s difficult or impossible for fallible human eyeballs to perform detailed scans of thousands of peas or nuts as they pass over a conveyor belt. 3-D machine vision offers a tool called “frame grabbing,” which takes stills of — potentially — tens of thousands of tiny, moving products at once to find flaws and perform sorting.
2. Automated Sorting for Large Product Batches
Machine vision inspection systems can easily become part of a much larger automation effort. Automation is a welcome addition to the food and beverage sector, translating into improved worker safety and efficiency and better quality control across the enterprise.
Inspection stations with machine vision cameras can scan single products or whole batches of products to detect flaws. But physically separating these products must be just as efficient a process as identifying them. For this reason, machine vision is an ideal companion to compressed air systems and others, which can carefully blow away and remove even a single grain of rice from a larger batch in preparation.
3. Near-Infrared Cameras
Machine vision takes many forms, including barcode and QR code readers. A newer technology, called near-infrared (NIR) cameras, is already substantially improving the usefulness and capabilities of machine vision.
Remember that bruised apple? Sometimes physical damage to fruits and vegetables doesn’t immediately appear on the outside. NIR technology expands the light spectrum cameras can observe, giving them the ability to detect interior damage before it shows up on the exterior. It represents a distinct advantage over previous-generation technology and human inspectors, both of which can leave flaws undiscovered.
Tips on Training Workers to Use Machine Vision
Implementing machine vision into a productive environment delivers major benefits, but it also comes with a potentially disruptive learning curve. The following are some ideas on how to navigate it.
1. Take Advantage of Third-Party Training Courses
Don’t expect employees to hit the ground running with machine vision if they’re not familiar with the fundamentals of how it works. Google has a crash course on machine learning, and Amazon offers a curriculum as well to help companies get their employees up to speed on the technology and how to use it.
2. Get the Lighting Right
Having the appropriate intensity of light shining on the food product is essential for the machine vision cameras to get a clear photo or video. The most common types of lighting for machine vision are quartz halogen, LEDs, metal halide and xenon lights. Metal halide and xenon are better for larger-scale operations because of their brightness.
Train employees to check the amount and positioning of the lighting before each inspection station starts up for the day, so that no shadows obscure products from view.
Machine vision does not involve buying a camera or two, setting them up, then slapping the “autopilot” button. As products turn over, and manufacturing and distribution environments change and grow over time, machine vision algorithms require re-training, and you might need to redesign the lighting setup.
Employers should find individuals from their ranks who show interest and aptitude in this technology and then invest in them as subject matter experts and process owners. Even if an outside vendor is the one providing libraries of algorithms and ultimately coming up with machine vision designs, every company needs a knowledgeable liaison who can align company needs with the products on the market.
It is important to remember that neither machine learning nor machine vision are about creating hardware that thinks and sees like humans do. With the right approach, these systems can roundly outperform human employees.
But first, companies need to recognize the opportunities. Then, they must match the available products to their unsolved problems and make sure their culture supports ongoing learning and the discovery of new aptitudes. Machine vision might be superior to human eyesight, but it uses decidedly human judgments as it goes about its work.
The plant-based meat market is anticipated to be worth more than $320 millionin the next five years, according to a report released last summer by Global Market Insights. As the popularity of meat-alternative products continues to rise, new challenges are being introduced to supply chain management. Joe Scioscia, vice president of sales at VAI explains some of these hurdles and proposes how technology can help.
Food Safety Tech: Is the growing popularity of plant-based foods introducing hazards or challenges to the supply chain?
Joe Scioscia: The growing popularity of plant-based foods has presented a new set of challenges for the supply chain, especially considering many of these organic items are being introduced by traditionally non-organic retailers. Impossible Foods received FDA approval for its plant-based burger in 2019, showing just how new the plant-based movement is to the industry.
Obviously, the organic supply chain and produce suppliers have long followed regulations for handling produce, such as temperature controls, cargo tracking, and supply and demand planning software, so the produce could be tracked from farm to table and in the case of a recall, be traced back to the source. But for meat alternatives that are combining multiple plant-based ingredients, organizations in the supply chain who are handling these products
have new food safety concerns. Considerations on how to store and process meat alternatives, how to treat each ingredient in the product and, most importantly, how to determine temperature controls or the source of contamination are all discussions the food industry is currently having.
FST: How are plant-based foods changing the dynamic of the supply chain from a food safety perspective?
Scioscia: The food supply chain has changed dramatically in recent years to become more complex, with food items traveling farther than ever before, containing more ingredients and required to follow stricter regulations. Many of the changes to the supply chain are for the better—organic and plant-based alternatives offer health benefits for consumers and are a move towards a more sustainable future. But the reality is that the supply chain isn’t quite there yet. Suppliers, retailers and producers at every part of the supply chain need to work together to ensure transparency and food safety compliance—including for plant-based products. Foodborne illnesses are still a real threat to the safety of consumers, and these same consumers are demanding transparency into the source of their food and sustainable practices from brands. All of these considerations are what’s making this next era of the food industry more complicated than ever before.
Because food safety compliance is always top of mind in the food industry to keep consumers safe, this new and complex supply chain has required companies to rely heavily on technology solutions to ensure plant-based products are equally as safe to consume as non-organic alternatives. These same solutions are also helping supply chains become more transparent for customers and streamline food processes to build a more sustainable future.
FST: What technologies can food companies and retailers use to better manage the supply chain risk while supporting the increased consumer demand for meat alternatives?
Scioscia: Utilizing a centralized software system is one tool many food suppliers and distributors can use to better visualize, trace and process products in the supply chain—including for plant-based alternatives. Having access to a central platform for business data to track assets and ensure food safety regulations are being met allows for companies to optimize processes and cut unnecessary costs along the way.
Heading into 2020, many organizations in the food supply chain are also looking at new applications like IoT, automation, and blockchain as ways to curb food safety issues. The FDA has taken steps to pilot blockchain and AI programs to better track drugs and food products, in conjunction with major food brands and technology companies. Other organizations are following suit with their own programs and many are looking at these solutions to improve their food tracking efforts. It’s clear technology has the most potential to make it easier on the industry to comply with food safety regulations while meeting customer demands for plant-based alternatives and organic options—all the while building a sustainable supply chain for the future.
Almost everybody loves chocolate, an ancient, basic, almost universal and primal source of pleasure. “The story of chocolate beings with cocoa trees that grew wild in the tropical rainforests of the Amazon basin and other areas in Central and South America for thousands of years… Christopher Columbus is said to have brought the first cocoa beans back to Europe from his fourth visit to the New World” between 1502 and 1504.1
Unfortunately, the production of chocolate and chocolate products today is as complex as any other global food product with supply chains that reach from one end of the world to the other. The complexity of the supply chain and production, along with the universal demand for the finished product, exposes chocolate to increasing pressure from numerous hazards, both unintentional and intentional. For example, we know that more than 70% of cocoa production takes place in West African countries, particularly the Ivory Coast and Ghana. These regions are politically unstable, and production is frequently disrupted by fighting. While production has started to expand into more stable regions, it has not yet become diversified enough to normalize the supply. About 17% of production takes place in the Americas (primarily South America) and 9% from Asia and Oceania.2
In today’s world of global commerce these pressures are not unique to chocolate. Food quality and safety experts should be armed with tools and innovations that can help them examine specific hazards and fraud pertaining to chocolate and chocolate products. In fact, the global nature of the chocolate market, requires fast reflexes that protect brand integrity and dynamic quality processes supported by informed decisions. Digital tools have become a necessity when a fast interpretation of dynamic data is needed. If a food organization is going to effectively protect the public’s health, protect their brand and comply with various governmental regulations and non-governmental standards such as GFSI, horizon scanning, along with the use of food safety intelligent digital tools, needs to be incorporated into food company’s core FSQA program.
This article pulls information from a recent industry report about chocolate products that presents an examination of the specific hazards and fraud pertaining to chocolate and chocolate products along with ways to utilize this information.
Cocoa and chocolate products rely on high quality ingredients and raw materials, strict supplier partnership schemes and conformity to clearly defined quality and safety standards. During the past 10 years there have been a significant number of food safety incidents associated with chocolate products. The presence of Salmonella enterica, Listeria monocytogenes, allergens and foreign materials in cocoa/chocolate products have been reported on a global scale. Today, information on food safety incidents and potential risks is quickly and widely available by way of the internet. However, because the pertinent data is frequently siloed, food safety professionals are unable to take full advantage of it.
Top Emerging Hazards: Chocolate Products (2013-2018)
Publicly available data, from sources such as European Union RASFF, Australian Competition and Consumer Commission, UK Food Standards Agency, FDA, Food Standards Australia New Zealand (FSANZ), shows a significant increase in identified food safety incidents for cocoa/chocolate products from 2013 to 2018. For this same time period, the top emerging hazards that were identified for chocolate products were the following:
Foreign bodies: 13.83%
Food additives & flavorings: 4.26%
Other hazards: 2.66%
By using such information to identify critical food safety protection trends, which we define to include food safety (unintentional adulteration) and food fraud (intentional adulteration, inclusive of authenticity/intentional misrepresentation) we can better construct our food protection systems to focus on the areas that present the greatest threats to public health, brand protection and compliance.
A Data Driven Approach
Monitoring Incoming Raw Materials
Assessment and identification of potential food protection issues, including food safety and fraud, at the stage of incoming raw materials is of vital importance for food manufacturers. Knowledge of the associated risks and vulnerabilities allows for timely actions and appropriate measures that may ultimately prevent an incident from occurring.
Specifically, the efficient utilization of global food safety and fraud information should allow for:
Identification of prevalent, increasing and/or emerging risks and vulnerabilities associated with raw materials
Comparative evaluation of the risk profile for different raw materials’ origins
Critical evaluation and risk-based selection of raw materials’ suppliers
A comprehensive risk assessment must start with the consideration of the identified food safety incidents of the raw material, which include the inherent characteristics of the raw material. Next, the origin-related risks must be taken into account and then the supplier-related risks must be examined. The full risk assessment is driven by the appropriate food safety data, its analysis and application of risk assessment scientific models on top of the data.
Using food safety intelligent digital tools to analyze almost 400 unique, chocolate product related food safety incidents around the globe provides us with important, useful insights about cocoa as a raw material, as a raw material from a specific origin and as a raw material being provided by specific suppliers. The graph below represents the results of the analysis illustrating the trend of incidents reported between 2002 and 2018. It can be observed that after a significant rise between 2009 and 2010, the number of incidents approximately doubled and remained at that level for the rest of the evaluated period (i.e., from 2010 to 2018), compared to the period from 2002 to 2005.
By further analyzing the data stemming from the 400 food safety incidents and breaking them down into more defined hazards, for incoming raw materials, we can clearly see that chemical hazards represent the major hazard category for cocoa.
Organoleptic aspects: 5.93%
Other Hazards: 4.38%
Foreign bodies: 2.06%
Food additives and flavorings: .77%
Food contact materials: .52%
Using the appropriate analytical tools, someone can drill down into the data and identify the specific incidents within the different hazard categories. For example, within the “chemical hazard” category specific hazards such as organophosphates, neonicotinoids, pyrethroids and organochlorines were identified.
Comparative Evaluation of Risk Profiles for Different Origins of Raw Materials
The main regions of origin for cocoa globally are Africa, Asia and South America. After collecting and analyzing all relevant data from recalls and border rejections and the frequency of pertinent incidents, we can accurately identify the top hazards for cocoa by region.
The top five specific hazards for the regions under discussion are listed in Table I.
Poor or insufficient controls
Table I. Top Five Hazards By Region
After the first level of analysis, a further interpretation of the data using the appropriate data intelligence tools can help to reach to very specific information on the nature of the incidents. This provides additional detail that is helpful in understanding how the regional risk profiles compare. For example, the prevalence of chemical contamination, as either industrial contaminants or pesticides, has been a commonly observed pattern for all three of the regions in Table I. However, beyond the general hazard category level, there are also different trends with regard to specific hazards for the three different regions. One such example is the increased presence of mold in cocoa beans coming from Africa.
The primary hazard categories for cocoa, as a raw ingredient were identified and a comparison among the primary hazards for cocoa by region (origin-specific) should take place. The next step in a data-powered supplier assessment workflow would be to incorporate our use of global food safety data in evaluating the suppliers of the raw materials.
The Role of Global Food Safety Data
This article has been focused on chocolate products but has only touched the surface in terms of the information available in the complete report, which also includes specific information about key raw materials. Let’s also be clear, that the techniques and tools used to generate this information are applicable to all food products and ingredients. As we strive to produce food safely in the 21st Century and beyond, we must adapt our methods or be left behind.
The regulatory environment the food industry must operate in has never been more intense. The threats to an organization’s brand have never been greater. This is not going to change. What must change is the way in which food companies confront these challenges.
Global food safety data can contribute to the establishment of an adaptive food safety/QA process that will provide time savings and improve a quality team’s efficiency and performance.
Based on the continuous analysis of food recalls and rejections by key national and international food authorities, a food safety / quality assurance manager could establish an adaptive supplier verification process and risk assessment process by utilizing the knowledge provided by such data. In that way, QA, procurement, food safety and quality departments can be empowered with critical supplier data that will inform the internal procedures for incoming materials and ingredients (e.g., raw materials, packaging materials) and allow for adaptive laboratory testing routines and compliance protocols. Moreover, food safety systems can become adaptive, enabling quality assurance and safety professionals to quickly update points of critical control when needed, and intervene in important stages of the chocolate manufacturing process.
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